A large quantity of published data is available only in the form of plots and it is often difficult to extract numerical data accurately out of these pictures. There are several softwares available to aid this process, but most are either paid or poorly written.
- - WebPlotDigitizer is the most popular Web-based alternative to Dagra.
- - WebPlotDigitizer is the most popular Open Source & free alternative to Dagra.
This open source, digitizing software converts an image file showing a graph or map, into numbers. The image file can come from a scanner, digital camera or screenshot. The numbers can be read on the screen, and written or copied to a spreadsheet.
- - Engauge Digitizer is the most popular Windows & Linux alternative to Dagra.
Engauge Digitizer Features
Plot Digitizer is a Java program used to digitize scanned plots of functional data. Often data is found presented in reports and references as functional X-Y type scatter or line plots. In order to use this data, it must somehow be digitized.
- - Plot Digitizer is the most popular Mac alternative to Dagra.
PlotDigitizer is data extraction software. It allows users to extract data points from graphs, plots, charts, and scanned documents.
GraphClick is a graph digitizer shareware for Mac OS X which allows to automatically retrieve the original (x,y)-data from the image of a scanned graphor fom QuickTime movies. Free download. Features automatic detection of solid, dashed or dotted lines, bar charts or symbols.
- - GraphClick is the most popular commercial alternative to Dagra.
Sometimes it is necessary to extract data values from graphs, e.g. in most scientific publications only plots but no data values are published. DigitizeIt makes it easy to actually get back numbers from such a plot!
jTechDig is a software tool written in Java for digitizing data from an image of graph or plot. jTechDig can import images from .gif, .bmp, .png etc. files. After mapping of the coordinates system the data can be digitized manually by clicking the mouse.
Take any graph or data from any source (Web or PDF document, for example), add your comments, and perform any manipulations, like nonlinear regression or curve fitting. Then print your results or export them to Excel or other database.
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